The invention relates to an adaptive equalizer and related method thereof, and more particularly, to an adaptive equalizer and related method capable of utilizing a weighted signal for controlling the adjustment weight of the equalization coefficients.
In communication systems, utilization of digital communication increases with each passing day. In order to raise the performance of the transmission device, it is important to overcome the non-ideal properties of the transmission channel. Common communication systems adopt equalizers in the front ends of receivers to decrease the effects of these non-ideal properties. The equalizer reduces the channel noise and other interference of the received data, so as to decode the received data more precisely. As a result, the transmission quality is guaranteed. Take the adaptive equalizer as an example, the adaptive equalizer utilizes a plurality of equalization coefficients to equalize a received signal, and adjusts the equalization coefficients according to the received signal and a reference signal. The reference signal may be a training sequence or a bit stream corresponding to a computing result of a slicer decoder or a Viterbi detector. The slicer decoder determines the received signal to be “0” or “1” by comparing the equalized signal with a slicing threshold. The Viterbi detector determines the received signal to be “0” or “1” by considering the relationship of a series of received data. Hence, the accuracy of the Viterbi detector is higher than the slicer decoder.
Please refer to FIG. 1. FIG. 1 is functional block diagram of a related art adaptive equalizer 10. The adaptive equalizer 10 comprises an equalization unit 12, a reference signal generator 14, and a coefficient adapting circuit 15. The coefficient adapting circuit 15 includes an error computing unit 16 and a coefficient computing unit 18. Firstly, the equalization unit 12 utilizes a plurality of equalization coefficients C0(0), C1(0), . . . , CN(0) to process a received signal y, and then generates an equalized signal yeq accordingly. The operation of the equalization unit 12 will be detailed in the following paragraph. Secondly, the reference signal generator 14 generates a desired signal ŷ by utilizing a training sequence, or by utilizing the bit stream d outputted by a slicer decoder or a Viterbi detector. Thirdly, the error computing unit 16 subtracts a desired signal ŷ from the equalized signal yeq to generate an error signal e. Finally, the coefficient computing unit 18 utilizes the received signal y and the error signal e to perform a Least Mean Square (LMS) operation to update the plurality of equalization coefficients to be C0(1), C1(1) . . . , CN(1). The equalization coefficients as C0, C1, . . . , CN will approach proper values by repeating the operation mentioned above several times. The operation of the related art coefficient computing unit 18 is represented in the following equation:Cj(k)=Cj(k−1)−τ·e(k)·y(k−j)  Equation (1)
In Equation (1), τ denotes a coefficient adjustment factor, which can be a predetermined value or an adjustable value relating to the channel environment. When the variation of the channel environment is very high, τ can be determined to be a greater number, which causes the equalization coefficients C0, C1, . . . , CN to be adjusted substantially and to enter a stable state (i.e. are convergent) quickly. On the contrary, if τ is set to be a smaller number, the equalization unit 12 will take more time to let the equalization coefficients C0, C1, . . . , CN enter the stable state. In addition, if τ is set to be a smaller number, the probability of the equalization coefficients C0, C1, . . . , CN not being convergent is reduced. Hence, the system error rate is reduced at the same time. As the equalization coefficients C0, C1, . . . , CN are updated several times, the error signal e approaches zero. As a result, the equalization coefficients C0, C1, . . . , CN enter the stable state. Until the channel environment changes, the error signal e increases, then the adaptive equalizer 10 adjusts the equalization coefficients C0, C1, . . . , CN utilized by the equalization unit 12 in the same manner.
Please refer to FIG. 2. FIG. 2 is schematic diagram of the equalization unit 12 shown in FIG. 1. The equalization unit 12 comprises a plurality of delay units 22, 24, 26, a plurality of multipliers 32, 34, 36, 38 with adjustable coefficients C0(k), C1(k), . . . , CN(k), and a plurality of adders 42, 44, 46. The delay time of the delay units 22, 24, 26 relate to the sampling time of the received signal y. The delay units 22, 24, 26 output a plurality of received signals y(k), y(k−1) . . . y(k−N) (i.e., delayed signals), respectively, corresponding to different sampling times. The multipliers 32, 34, 36, 38 respectively multiply the adjustable equalization coefficients C0(k), C1(k), . . . , CN(k) by the corresponding delay signals y(k), y(k−1) . . . y(k−N). The sum of the multiplication result is the equalized signal yeq. The operation of the equalization unit 12 is shown in the following equation:yeq(k)=C0·y(k)+C1·y(k−1)+ . . . CN·y(k−N)  Equation (2)
In practice, the error rates of certain received data, and more particularly the received data with level transition, are higher than other received data. However, the related art adaptive equalizers do not address the problem mentioned above. Therefore, if the error rates of the certain received data mentioned above are reduced, the averaged error rates of the communication systems are improved significantly.